metadata
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.3
tags:
- axolotl
- generated_from_trainer
datasets:
- representation_variation_GAIA_Raw_Training_Data.jsonl
- text_chunks_GAIA_Raw_Training_Data.jsonl
- inferred_facts_GAIA_Raw_Training_Data.jsonl
model-index:
- name: test-model-1-pretrain
results: []
See axolotl config
axolotl version: 0.8.0.dev0
base_model: mistralai/Mistral-7B-Instruct-v0.3
tokenizer_type: AutoTokenizer
model_type: AutoModelForCausalLM
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: representation_variation_GAIA_Raw_Training_Data.jsonl
type: completion
- path: text_chunks_GAIA_Raw_Training_Data.jsonl
type: completion
- path: inferred_facts_GAIA_Raw_Training_Data.jsonl
type: completion
dataset_prepared_path: last_run_prepared
output_dir: ./model-output
seed: 1337
sequence_len: 5000
sample_packing: true
pad_to_sequence_len: false
shuffle_merged_datasets: true
gradient_accumulation_steps: 75
micro_batch_size: 2
eval_batch_size: 4
num_epochs: 7
optimizer: paged_adamw_8bit
lr_scheduler: constant
learning_rate: 2.0e-05
noisy_embedding_alpha: 5
weight_decay: 0
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
logging_steps: 1
xformers_attention: false
flash_attention: false
chat_template: chatml
auto_resume_from_checkpoints: false
warmup_ratio: 0.1
evals_per_epoch: 1
val_set_size: 0.04
saves_per_epoch: 1
eval_sample_packing: false
save_total_limit: 2
special_tokens:
pad_token: <unk>
use_liger_kernel: true
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_layer_norm: true
liger_fused_linear_cross_entropy: true
sequence_length: 10000
wandb_project: test-project
wandb_entity: ""
wandb_watch: ""
wandb_run_id: ""
wandb_log_model: ""
hub_model_id: Jboadu/test-model-1-pretrain
hub_strategy: all_checkpoints
test-model-1-pretrain
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the representation_variation_GAIA_Raw_Training_Data.jsonl, the text_chunks_GAIA_Raw_Training_Data.jsonl and the inferred_facts_GAIA_Raw_Training_Data.jsonl datasets. It achieves the following results on the evaluation set:
- Loss: 1.2857
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 1337
- gradient_accumulation_steps: 75
- total_train_batch_size: 150
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 7.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7564 | 0.7426 | 1 | 2.1477 |
| 4.0475 | 1.7426 | 2 | 2.0678 |
| 3.5711 | 2.7426 | 3 | 2.3400 |
| 3.3781 | 3.7426 | 4 | 1.9086 |
| 3.2075 | 4.7426 | 5 | 1.6236 |
| 2.3991 | 5.7426 | 6 | 1.4519 |
| 2.1077 | 6.7426 | 7 | 1.2857 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0